Assessment of Decontamination and Reuse of Disposable Filter Funnels Used in Microbiological Water Quality Tests
Bibliographic record
Abstract
into nationally-representative household surveys such as the Multiple Indicator Cluster Surveys (MICS). However, plastic waste generated during such water quality testing programs, mostly through the use of pre-sterilized disposable materials, is non-negligible. The objective of this study was to evaluate several re-use protocols for disposable filter funnels used by the MICS water quality test kits. Decontamination and re-use protocols were assessed in centralized laboratory and decentralized field settings and neither yielded positive results. Re-use of 100 mL sterile funnels decontaminated with an alcohol wipe resulted in a higher incidence of false positive results (i.e., positive contamination when processing sterile water), both in the laboratory and field; therefore, a higher proportion of positives tests can be expected if these components are re-used. Further improvements to the decontamination technique and training are needed before material re-use can be reliably adopted. Autoclaving the funnels for re-use is feasible, provided that there is capacity to re-package and distribute funnels in a sterile manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".